RNA interference screening methods to identify proliferation determinants and mechanisms of resistance to immune attack.

We have used RNA interference (RNAi) screening technology to reveal unknown components of biological signaling pathways including survival mechanisms of estrogen-independent breast cancer cell growth and cancer cell resistance to immune attack. In this chapter, a detailed protocol describing the use of RNAi screening to identify factors important for the proliferation of estrogen-independent MCF7 breast cancer cells will be described. Resistance to therapies that target the estrogen pathway remains a challenge in the treatment of estrogen receptor-positive breast cancer. To address this challenge, small interfering-RNA (siRNA)-based libraries targeting an estrogen receptor (ER)- and aromatase-centered network, including 631 genes relevant to estrogen signaling, was designed and constructed for RNAi screening. This protocol will include the following parts: (1) selection of RNAi transfection reagent for specific cells; (2) optimization of RNAi screening conditions using Z'-factor; (3) procedure of ER-network gene siRNA library screening using automated machines under optimized experimental conditions; and (4) method of analysis for RNAi screening data to identify specific determinants important for cell proliferation. 46 genes were found to be selectively required for the survival of estrogen-independent MCF7-derived cells.

RNA Interference Screening to Identify Proliferation Determinants in Breast Cancer Cells.

RNAi screening technology has revealed unknown determinants of various biological signaling pathways in biomedical studies. This protocol provided detailed information about how to use RNAi screening to identify proliferation determinants in breast tumor cells. siRNA-based libraries targeting against Estrogen receptor (ER)-network, including 631 genes relevant to estrogen signaling, was constructed for screening in breast cancer cells. Briefly, reverse transfection of siRNA induced transient gene knockdown in MCF7 cells. First, the transfection reagent for MCF7 cells was selected. Next, the Z'-score assay was used to monitor if screening conditions yielded efficiently. Then, the ER-network siRNA library screening was preceded by automatic machines under optimized experimental conditions.

c-Abl modulates tumor cell sensitivity to antibody-dependent cellular cytotoxicity.

Monoclonal antibodies (mAb) can modulate cancer cell signal transduction and recruit antitumor immune effector mechanisms-including antibody-dependent cellular cytotoxicity (ADCC). Although several clinically effective antibodies can promote ADCC, therapeutic resistance is common. We hypothesized that oncogenic signaling networks within tumor cells affect their sensitivity to ADCC. We developed a screening platform and targeted 60 genes derived from an EGFR gene network using RNAi in an in vitro ADCC model system. Knockdown of GRB7, PRKCE, and ABL1 enhanced ADCC by primary and secondary screens. ABL1 knockdown also reduced cell proliferation, independent of its ADCC enhancement effects. c-Abl overexpression decreased ADCC sensitivity and rescued the effects of ABL1 knockdown. Imatinib inhibition of c-Abl kinase activity also enhanced ADCC-phenocopying ABL1 knockdown-against several EGFR-expressing head-and-neck squamous cell carcinoma cell lines by ex vivo primary natural killer cells. Our findings suggest that combining c-Abl inhibition with ADCC-promoting antibodies, such as cetuximab, could translate into increased therapeutic efficacy of mAbs.

Synthetic lethal screen of an EGFR-centered network to improve targeted therapies.

Intrinsic and acquired cellular resistance factors limit the efficacy of most targeted cancer therapeutics. Synthetic lethal screens in lower eukaryotes suggest that networks of genes closely linked to therapeutic targets would be enriched for determinants of drug resistance. We developed a protein network centered on the epidermal growth factor receptor (EGFR), which is a validated cancer therapeutic target, and used small interfering RNA screening to comparatively probe this network for proteins that regulate the effectiveness of both EGFR-targeted agents and nonspecific cytotoxic agents. We identified subnetworks of proteins influencing resistance, with putative resistance determinants enriched among proteins that interacted with proteins at the core of the network. We found that clinically relevant drugs targeting proteins connected in the EGFR network, such as protein kinase C or Aurora kinase A, or the transcriptional regulator signal transducer and activator of transcription 3 (STAT3), synergized with EGFR antagonists to reduce cell viability and tumor size, suggesting the potential for a direct path to clinical exploitation. Such a focused approach can potentially improve the coherent design of combination cancer therapies.

Mechanisms of tumor resistance to EGFR-targeted therapies.

BACKGROUND: Much effort has been devoted to development of cancer therapies targeting EGFR, based on its role in regulating cell growth. Small-molecule and antibody EGFR inhibitors have clinical roles based on their efficacy in a subset of cancers, generally as components of combination therapies. Many cancers are either initially resistant to EGFR inhibitors or become resistant during treatment, limiting the efficacy of these reagents. OBJECTIVE/METHODS: To review cellular resistance mechanisms to EGFR-targeted therapies. RESULTS/CONCLUSIONS: The best validated of these mechanisms include activation of classic ATP-binding casette (ABC) multidrug transporters; activation or mutation of EGFR; and overexpression or activation of signaling proteins operating in relation to EGFR. We discuss current efforts and potential strategies to override these sources of resistance. We describe emerging systems-biology-based concepts of alternative resistance to EGFR-targeted therapies, and discuss their implications for use of EGFR-targeted and other targeted therapies.